Journal articles on the topic 'IoT Cloud'
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Han, Jungsu, Sun Park, and JongWon Kim. "Dynamic OverCloud: Realizing Microservices-Based IoT-Cloud Service Composition over Multiple Clouds." Electronics 9, no. 6 (June 11, 2020): 969. http://dx.doi.org/10.3390/electronics9060969.
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With the expansion of cloud-leveraged Information and Communications Technology (ICT) convergence trend, cloud-native computing is starting to be the de-facto paradigm together with MSA(Microservices Architecture)-based service composition for agility and efficiency. Moreover, by bridging the Internet of Things (IoT) and cloud together, a variety of cloud applications are explosively emerging. As an example, the so-called IoT-Cloud services, which are cloud-leveraged inter-connected services with distributed IoT devices, dynamically utilize geographically-distributed multiple clouds since mobile IoT devices can selectively connect to the near-by cloud resources for low-latency and high-throughput connectivity. In comparison, most public cloud providers may cause vendor lock-in problems that limit the inter-operable service compositions. Thus, in this paper, we propose a new overlay approach to address the above limitations, denoted as Dynamic OverCloud, which is a specially-arranged razor-thin overlay layer that provides users with an inter-operable and visibility-supported environment for MSA-based IoT-Cloud service composition over the existing multiple clouds. Then, we design a software framework that dynamically builds the proposed concept. We also describe a detailed implementation of the software framework with workflows. Finally, we verify its feasibility by realizing a smart energy IoT-Cloud service with the suggested operation lifecycle.
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Mohammed Sadeeq, Mohammed, Nasiba M. Abdulkareem, Subhi R. M. Zeebaree, Dindar Mikaeel Ahmed, Ahmed Saifullah Sami, and Rizgar R. Zebari. "IoT and Cloud Computing Issues, Challenges and Opportunities: A Review." Qubahan Academic Journal 1, no. 2 (March 15, 2021): 1–7. http://dx.doi.org/10.48161/qaj.v1n2a36.
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With the exponential growth of the Industrial Internet of Things (IIoT), multiple outlets are constantly producing a vast volume of data. It is unwise to locally store all the raw data in the IIoT devices since the energy and storage spaces of the end devices are strictly constrained. self-organization and short-range Internet of Things (IoT) networking also support outsourced data and cloud computing, independent of the distinctive resource constraint properties. For the remainder of the findings, there is a sequence of unfamiliar safeguards for IoT and cloud integration problems. The delivery of cloud computing is highly efficient, storage is becoming more and more current, and some groups are now altering their data from in house records Cloud Computing Vendors' hubs. Intensive IoT applications for workloads and data are subject to challenges while utilizing cloud computing tools. In this report, we research IoT and cloud computing and address cloud-compatible problems and computing techniques to promote the stable transition of IoT programs to the cloud.
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Yangui, Sami. "A Panorama of Cloud Platforms for IoT Applications Across Industries." Sensors 20, no. 9 (May 9, 2020): 2701. http://dx.doi.org/10.3390/s20092701.
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Internet of Things (IoT) applications can play a critical role in business and industry. Industrial IoT (IIoT) refers to the use of IoT technologies in manufacturing. Enabling IIoT applications in cloud environments requires the design of appropriate IIoT Platform as-a-Service (IIoT PaaS) to support and ease their provisioning (i.e., development, deployment and management). This paper critically reviews the IIoT PaaS architectures proposed so far in the relevant literature. It only surveys the architectures that are suitable for IIoT applications provisioning and it excludes regular IoT solutions from its scope. The evaluation is based on a set of well-defined architectural requirements. It also introduces and discusses the future challenges and the research directions. The critical review discusses the PaaS solutions that focus on the whole spectrum of IoT verticals and also the ones dealing with specific IoT verticals. Existing limitations are identified and hints are provided on how to tackle them. As critical research directions, the mechanisms that enable the secure provisioning, and IIoT PaaS interaction with virtualized IoT Infrastructure as-a-Service (IaaS) and fog computing layer are discussed.
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Hamann, Ulrich, and Matthias Reinwarth. "Cloud und IoT." Digitale Welt 2, no. 2 (March 7, 2018): 52–54. http://dx.doi.org/10.1007/s42354-018-0077-3.
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Chen, Fei, Duming Luo, Tao Xiang, Ping Chen, Junfeng Fan, and Hong-Linh Truong. "IoT Cloud Security Review." ACM Computing Surveys 54, no. 4 (May 2021): 1–36. http://dx.doi.org/10.1145/3447625.
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Recent years have seen the rapid development and integration of the Internet of Things (IoT) and cloud computing. The market is providing various consumer-oriented smart IoT devices; the mainstream cloud service providers are building their software stacks to support IoT services. With this emerging trend even growing, the security of such smart IoT cloud systems has drawn much research attention in recent years. To better understand the emerging consumer-oriented smart IoT cloud systems for practical engineers and new researchers, this article presents a review of the most recent research efforts on existing, real, already deployed consumer-oriented IoT cloud applications in the past five years using typical case studies. Specifically, we first present a general model for the IoT cloud ecosystem. Then, using the model, we review and summarize recent, representative research works on emerging smart IoT cloud system security using 10 detailed case studies, with the aim that the case studies together provide insights into the insecurity of current emerging IoT cloud systems. We further present a systematic approach to conduct a security analysis for IoT cloud systems. Based on the proposed security analysis approach, we review and suggest potential security risk mitigation methods to protect IoT cloud systems. We also discuss future research challenges for the IoT cloud security area.
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Rashid Abdulqadir, Hindreen, Subhi R. M. Zeebaree, Hanan M. Shukur, Mohammed Mohammed Sadeeq, Baraa Wasfi Salim, Azar Abid Salih, and Shakir Fattah Kak. "A Study of Moving from Cloud Computing to Fog Computing." Qubahan Academic Journal 1, no. 2 (April 27, 2021): 60–70. http://dx.doi.org/10.48161/qaj.v1n2a49.
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The exponential growth of the Internet of Things (IoT) technology poses various challenges to the classic centralized cloud computing paradigm, including high latency, limited capacity, and network failure. Cloud computing and Fog computing carry the cloud closer to IoT computers in order to overcome these problems. Cloud and Fog provide IoT processing and storage of IoT items locally instead of sending them to the cloud. Cloud and Fog provide quicker reactions and better efficiency in conjunction with the cloud. Cloud and fog computing should also be viewed as the safest approach to ensure that IoT delivers reliable and stable resources to multiple IoT customers. This article discusses the latest in cloud and Fog computing and their convergence with IoT by stressing deployment's advantages and complexities. It also concentrates on cloud and Fog design and new IoT technologies, enhanced by utilizing the cloud and Fog model. Finally, transparent topics are addressed, along with potential testing recommendations for cloud storage and Fog computing, and IoT.
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Ahmad, Aftab, Ravi Mukkamala, and Karthik Navuluri. "Privacy in IoT Cloud." Athens Journal of Τechnology & Engineering 5, no. 4 (November 27, 2018): 377–92. http://dx.doi.org/10.30958/ajte.5-4-4.
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Jeong, Yoon-Su, and Sung-Ho Sim. "Hierarchical Multipath Blockchain Based IoT Information Management Techniques for Efficient Distributed Processing of Intelligent IoT Information." Sensors 21, no. 6 (March 14, 2021): 2049. http://dx.doi.org/10.3390/s21062049.
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As cloud technology advances, devices such as IoT (Internet of Things) are being utilized in various areas ranging from transportation, manufacturing, energy, automation, space, defense, and healthcare. As the number of IoT devices increases, the safety of IoT information, which is vulnerable to cyber attacks, is emerging as an important area of interest in distributed cloud environments. However, integrity techniques are not guaranteed to easily identify the integrity threats and attacks on IoT information operating in the distributed cloud associated with IoT systems and CPS (Cyber-Physical System). In this paper, we propose a blockchain-based integrity verification technique in which large amounts of IoT information processed in distributed cloud environments can be guaranteed integrity in security threats related to IoT systems and CPS. The proposed technique aims to ensure the integrity of IoT information by linking information from IoT devices belonging to subgroups in distributed cloud environments to information from specific non-adjacent IoT devices and blockchain. This is because existing techniques rely on third-party organizations that the data owner can trust to verify the integrity of the data. The proposed technique identifies IoT information by connecting the paths of IoT pre- and subsequent blocks into block chains so that synchronization can be achieved between subgroups in distributed cloud environments. Furthermore, the proposed technique uses probabilistic similarity information between IoT information blocks to react flexibly to subgroups that constitute distributed clouds so that IoT information blocks are not exploited maliciously by third parties. As a result of performance evaluation, the proposed technique averaged 12.3% improvement in integrity processing time over existing techniques depending on blockchain size. Furthermore, the proposed technique has to hash the IoT information that constitutes a subgroup with probability-linked information, validating the integrity of large-capacity IoT information, resulting in an average of 8.8% lower overhead than existing techniques. In addition, the proposed technique has an average improvement of 14.3% in blockchain-based integrity verification accuracy over existing techniques, depending on the hash chain length.
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Hick, Lukas, Dirk Börner, and Henning Pagnia. "Cloud to Cloud Integration im IoT Umfeld." HMD Praxis der Wirtschaftsinformatik 56, no. 6 (November 1, 2019): 1204–19. http://dx.doi.org/10.1365/s40702-019-00565-y.
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Ahuja, Sanjay P., and Niharika Deval. "From Cloud Computing to Fog Computing." International Journal of Fog Computing 1, no. 1 (January 2018): 1–14. http://dx.doi.org/10.4018/ijfc.2018010101.
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This article describes how in recent years, Cloud Computing has emerged as a fundamental computing paradigm that has significantly changed the approach of enterprises as well as end users towards implementation of Internet technology. The key characteristics such as on-demand resource provision, scalability, rapid elasticity, higher flexibility, and significant cost savings have influenced enterprises of all sizes in the wide and successful adoption of Cloud Computing. Despite numerous advantages, Cloud Computing has its fair share of downsides as well. One of those major concerns is latency issues which has relevance to the Internet of Things (IoT). A new computing paradigm has been proposed by Cisco in early 2014 and termed 'Fog Computing'. Fog Computing otherwise known as Edge Computing is the integration of Cloud Computing and IoT. Being located in close proximity to the IoT devices, the Fog assists with latency requirements of IoT related applications. It also meets the data processing needs of IoT devices which are resource constrained by bringing computation, communication, control and storage closer to the end users. Clouds continue to offer support for data analytics. One can think of the IoT-Fog-Cloud as being part of a continuum. This article surveys the current literature on Fog Computing and provides a discussion on the background, details and architecture of Fog Computing, as well as the application areas of Fog Computing. The article concludes with some recommendations in the areas of future research.
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Dwivedi, Sanjeev Kumar, Priyadarshini Roy, Chinky Karda, Shalini Agrawal, and Ruhul Amin. "Blockchain-Based Internet of Things and Industrial IoT: A Comprehensive Survey." Security and Communication Networks 2021 (August 23, 2021): 1–21. http://dx.doi.org/10.1155/2021/7142048.
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Industry 4.0 connects the latest technologies such as cloud computing, Internet of things (IoT), machine learning and artificial intelligence (ML/AI), and blockchain to provide more automation in the industrial process and also bridges the gap between the physical and digital worlds through the cyber-physical system. The inherent feature of IoT devices creates the industry to smart industry (referred to as industrial IoT, i.e., IIoT) through its data-driven decision policies. However, several challenges such as decentralization, security and privacy vulnerability, single point of failure (SPOF), and trust issues exist in the IoT system. Blockchain is one of the promising technologies that can bring about opportunities for addressing the challenges of IoT systems. In this article, we have investigated the integration of IoT with blockchain technology and provided an in-depth study of the blockchain-enabled IoT and IIoT systems. The state-of-the-art research is categorized into data storage and management technique, big data and cloud computing technique (finance and data auditing), and industrial sectors (supply chain, energy, and healthcare sector). The insightful discussion based on the different categories is also presented in the paper. In particular, first, we introduce the IoT and IIoT and then discuss the need for smart contracts in IoT and IIoT systems. Next, we concentrate on the convergence of blockchain and IoT with state-of-the-art research. In addition, this article also provides the open and future research directions towards this era with the highlighted observations.
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De Donno, Michele, Alberto Giaretta, Nicola Dragoni, Antonio Bucchiarone, and Manuel Mazzara. "Cyber-Storms Come from Clouds: Security of Cloud Computing in the IoT Era." Future Internet 11, no. 6 (June 4, 2019): 127. http://dx.doi.org/10.3390/fi11060127.
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The Internet of Things (IoT) is rapidly changing our society to a world where every “thing” is connected to the Internet, making computing pervasive like never before. This tsunami of connectivity and data collection relies more and more on the Cloud, where data analytics and intelligence actually reside. Cloud computing has indeed revolutionized the way computational resources and services can be used and accessed, implementing the concept of utility computing whose advantages are undeniable for every business. However, despite the benefits in terms of flexibility, economic savings, and support of new services, its widespread adoption is hindered by the security issues arising with its usage. From a security perspective, the technological revolution introduced by IoT and Cloud computing can represent a disaster, as each object might become inherently remotely hackable and, as a consequence, controllable by malicious actors. While the literature mostly focuses on the security of IoT and Cloud computing as separate entities, in this article we provide an up-to-date and well-structured survey of the security issues of cloud computing in the IoT era. We give a clear picture of where security issues occur and what their potential impact is. As a result, we claim that it is not enough to secure IoT devices, as cyber-storms come from Clouds.
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Ghayvat, Hemant, S. C. Mukhopadhyay, Jie Liu, Arun Babu, Eshrat Elahi, and Xiang Gui. "Internet of Things for smart homes and buildings: Opportunities and Challenges." Australian Journal of Telecommunications and the Digital Economy 3, no. 4 (December 29, 2015): 33. http://dx.doi.org/10.18080/ajtde.v3n4.23.
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Pervasive sensing facilitated by Wireless Sensor Networks (WSNs) technologies offered the integration of modern technology into a daily routine. The smart sensing approach offers the ability to sense the ambient parameters and use of different objects in the urban environment. Identification and monitoring technologies, WSNs, wireless communication protocols, and dispersed intelligence for objects are primitive elements of smart environmental solution. The WSNs with the application of Internet of Things (IoT) and Cloud Computing are uplifting the smart home solutions and applications. The present research work aims to develop smart home and building solutions based on IoT and cloud computing. The cloud implementation using free cloud space, which is based on collaboration between public and private clouds, is presented. Additionally the research work recorded recent practical challenges and limitations encounter while designing the IoT-based smart environment. The research identifies the IoT idea through the conjunction of WSNs, the internet and distributed computing with data mining and machine learning an approach to apply at smart home to benefit and humankind.
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Ghayvat, Hemant, S. C. Mukhopadhyay, Jie Liu, Arun Babu, Eshrat Elahi, and Xiang Gui. "Internet of Things for smart homes and buildings: Opportunities and Challenges." Journal of Telecommunications and the Digital Economy 3, no. 4 (December 29, 2015): 33–47. http://dx.doi.org/10.18080/jtde.v3n4.23.
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Pervasive sensing facilitated by Wireless Sensor Networks (WSNs) technologies offered the integration of modern technology into a daily routine. The smart sensing approach offers the ability to sense the ambient parameters and use of different objects in the urban environment. Identification and monitoring technologies, WSNs, wireless communication protocols, and dispersed intelligence for objects are primitive elements of smart environmental solution. The WSNs with the application of Internet of Things (IoT) and Cloud Computing are uplifting the smart home solutions and applications. The present research work aims to develop smart home and building solutions based on IoT and cloud computing. The cloud implementation using free cloud space, which is based on collaboration between public and private clouds, is presented. Additionally the research work recorded recent practical challenges and limitations encounter while designing the IoT-based smart environment. The research identifies the IoT idea through the conjunction of WSNs, the internet and distributed computing with data mining and machine learning an approach to apply at smart home to benefit and humankind.
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Bangui, Hind, Said Rakrak, Said Raghay, and Barbora Buhnova. "Moving to the Edge-Cloud-of-Things: Recent Advances and Future Research Directions." Electronics 7, no. 11 (November 8, 2018): 309. http://dx.doi.org/10.3390/electronics7110309.
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Cloud computing has significantly enhanced the growth of the Internet of Things (IoT) by ensuring and supporting the Quality of Service (QoS) of IoT applications. However, cloud services are still far from IoT devices. Notably, the transmission of IoT data experiences network issues, such as high latency. In this case, the cloud platforms cannot satisfy the IoT applications that require real-time response. Yet, the location of cloud services is one of the challenges encountered in the evolution of the IoT paradigm. Recently, edge cloud computing has been proposed to bring cloud services closer to the IoT end-users, becoming a promising paradigm whose pitfalls and challenges are not yet well understood. This paper aims at presenting the leading-edge computing concerning the movement of services from centralized cloud platforms to decentralized platforms, and examines the issues and challenges introduced by these highly distributed environments, to support engineers and researchers who might benefit from this transition.
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Persson, Per, and Ola Angelsmark. "Calvin – Merging Cloud and IoT." Procedia Computer Science 52 (2015): 210–17. http://dx.doi.org/10.1016/j.procs.2015.05.059.
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Yang, Hyunsik, and Younghan Kim. "Design and Implementation of Fast Fault Detection in Cloud Infrastructure for Containerized IoT Services." Sensors 20, no. 16 (August 16, 2020): 4592. http://dx.doi.org/10.3390/s20164592.
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The container-based cloud is used in various service infrastructures as it is lighter and more portable than a virtual machine (VM)-based infrastructure and is configurable in both bare-metal and VM environments. The Internet-of-Things (IoT) cloud-computing infrastructure is also evolving from a VM-based to a container-based infrastructure. In IoT clouds, the service availability of the cloud infrastructure is more important for mission-critical IoT services, such as real-time health monitoring, vehicle-to-vehicle (V2V) communication, and industrial IoT, than for general computing services. However, in the container environment that runs on a VM, the current fault detection method only considers the container’s infra, thus limiting the level of availability necessary for the performance of mission-critical IoT cloud services. Therefore, in a container environment running on a VM, fault detection and recovery methods that consider both the VM and container levels are necessary. In this study, we analyze the fault-detection architecture in a container environment and designed and implemented a Fast Fault Detection Manager (FFDM) architecture using OpenStack and Kubernetes for realizing fast fault detection. Through performance measurements, we verified that the FFDM can improve the fault detection time by more than three times over the existing method.
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Javaid, Sabeen, Hammad Afzal, Muhammad Babar, Fahim Arif, Zhiyuan Tan, and Mian Ahmad Jan. "ARCA-IoT: An Attack-Resilient Cloud-Assisted IoT System." IEEE Access 7 (2019): 19616–30. http://dx.doi.org/10.1109/access.2019.2897095.
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Aleisa, Mohammed A., Abdullah Abuhussein, Faisal S. Alsubaei, and Frederick T. Sheldon. "Novel Security Models for IoT–Fog–Cloud Architectures in a Real-World Environment." Applied Sciences 12, no. 10 (May 10, 2022): 4837. http://dx.doi.org/10.3390/app12104837.
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With the rise of the Internet of Things (IoT), there is a demand for computation at network edges because of the limited processing capacity of IoT devices. Fog computing is a middle layer that has appeared to address the latency issues between the Internet of things (IoT) and the cloud. Fog computing is becoming more important as companies face increasing challenges in collecting and sending data from IoT devices to the cloud. However, this has led to new security and privacy issues as a result of the large number of sensors in IoT environments as well as the massive amount of data that must be analyzed in real time. To overcome the security challenges between the IoT layer and fog layer and, thus, meet the security requirements, this paper proposes a fine-grained data access control model based on the attribute-based encryption of the IoT–Fog–Cloud architecture to limit the access to sensor data and meet the authorization requirements. In addition, this paper proposes a blockchain-based certificate model for the IoT–Fog–Cloud architecture to authenticate IoT devices to fog devices and meet the authentication requirements. We evaluated the performance of the two proposed security models to determine their efficiency in real-life experiments of the IoT–Fog–Cloud architecture. The results demonstrate that the performance of the IoT–Fog–Cloud architecture with and without the blockchain-based certificate model was the same when using one, two, or three IoT devices. However, the performance of the IoT–Fog–Cloud architecture without the access control model was slightly better than that of the architecture with the model when using one, two, or three IoT devices.
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R, Prof Madhu B., Vaishnavi K. R, and Dushyanth N. Gowda. "IoT Based Home Automation System over Cloud." International Journal of Trend in Scientific Research and Development Volume-3, Issue-4 (June 30, 2019): 966–68. http://dx.doi.org/10.31142/ijtsrd24005.
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Ren, Jie, and Lijuan Liu. "A Study on Information Classification and Storage in Cloud Computing Data Centers Based on Group Collaborative Intelligent Clustering." Journal of Electrical and Computer Engineering 2022 (March 25, 2022): 1–11. http://dx.doi.org/10.1155/2022/1476661.
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Internet of things (IoT) and cloud computing are combined to form a cloud computing data center, and cloud computing provides virtualization, storage, computing, and other support services for IoT applications. Data is the foundation and core of cloud IoT platform applications, and massive multisource heterogeneous IoT data aggregation and storage have basic requirements such as real-time, security, and scalability. This paper focuses on the aggregation and storage methods of massive heterogeneous cloud IoT data, solving the multisource data aggregation problem caused by inconsistent protocols and the heterogeneous data storage problem caused by inconsistent data types. A heterogeneous network protocol adaptation and data aggregation method is proposed for the multisource data aggregation problem caused by protocol inconsistency. A protocol adaptation layer is set up in the IoT virtual gateway to achieve compatibility with multiple types of data aggregation protocols, ensuring adaptive access to different types of IoT nodes, and on this basis, data is transmitted to the cloud IoT platform through a unified interface, shielding the variability of IoT sensing devices. Given the problems of device forgery and malicious tampering in the data aggregation process, we propose a fast authentication and data storage method for IoT devices based on “API key” and implant the device authentication API key into the protocol adaptation layer of the virtual gateway to realize the source authentication of IoT nodes and ensure the authenticity of data.
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Rababah, Baha, and Rasit Eskicioglu. "Distributed Intelligence Model for IoT Applications Based on Neural Networks." International Journal of Computer Network and Information Security 13, no. 3 (June 8, 2021): 1–14. http://dx.doi.org/10.5815/ijcnis.2021.03.01.
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Increasing the implication of IoT data puts a focus on extracting the knowledge from sensors’ raw data. The management of sensors’ data is inefficient with current solutions, as studies have generally focused on either providing cloud-based IoT solutions or inefficient predefined rules. Cloud-based IoT solutions have problems with latency, availability, security and privacy, and power consumption. Therefore, Providing IoT gateways with relevant intelligence is essential for gaining knowledge from raw data to make the decision of whether to actuate or offload tasks to the cloud. This work proposes a model that provides an IoT gateway with the intelligence needed to extract the knowledge from sensors’ data in order to make the decision locally without needing to send all raw data to the cloud over the Internet. This speeds up decisions and actions for real-time data and overcomes the limitations of cloud-based IoT solutions. When the gateway is unable to process a task locally, the data and task are offloaded to the cloud.
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Benedict, Shajulin, and Michael Gerndt. "Introduction to the Special Issue on IoT Cloud Solutions for Societal Applications." Scalable Computing: Practice and Experience 20, no. 3 (September 22, 2019): iii. http://dx.doi.org/10.12694/scpe.v20i3.1323.
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Addressing societal problems such as air pollution, water contamination, corruption, healthcare management, agricultural assistance, and so forth has increased in the recent past using several highend technologies, including IoT cloud.
In fact, innovations have become the key factor of economic growth in several developing and developed countries. For instance, Atal Innovation Mission of India has promoted innovations that addresses the needs of the society through IoT cloud based technologies at AIC-IIITKottayam; TUM-Germany and several top ranked universities across the globe have driven the research or product developments targeting the benefits of the society – energy, healthcare, agriculture, economic health, and so forth.
Existing IoT based societal applications require a large volume of data for the analysis; a secure environment for handling data (either in the cloud or edge environments); and, a diligent planning while handling heterogeneous devices on federated cloud environments. In fact, scalability of cloud resources is the backbone for IoT cloud environments, while edge computing is required for short response times. Many IoT applications are based on automatic decision making applying machine learning on huge data sets and thus, these techniques influenced a large group of researchers in the IoT cloud domain.
This special issue on “IoT Cloud Solutions for Societal Applications” discusses security aspects and a decision making in IoT applications. Syed et al discuss IoT security requirements, challenges, and in the context of smart cities, smart health, smart building, smart transport, and smart industry applications; Naveen et al have carried out a theoretical evaluation using spacio-temporal distance networks in a deep learning network in order to perform the action recognition tasks in IoT environments.
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Atlam, Hany, Robert Walters, and Gary Wills. "Fog Computing and the Internet of Things: A Review." Big Data and Cognitive Computing 2, no. 2 (April 8, 2018): 10. http://dx.doi.org/10.3390/bdcc2020010.
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With the rapid growth of Internet of Things (IoT) applications, the classic centralized cloud computing paradigm faces several challenges such as high latency, low capacity and network failure. To address these challenges, fog computing brings the cloud closer to IoT devices. The fog provides IoT data processing and storage locally at IoT devices instead of sending them to the cloud. In contrast to the cloud, the fog provides services with faster response and greater quality. Therefore, fog computing may be considered the best choice to enable the IoT to provide efficient and secure services for many IoT users. This paper presents the state-of-the-art of fog computing and its integration with the IoT by highlighting the benefits and implementation challenges. This review will also focus on the architecture of the fog and emerging IoT applications that will be improved by using the fog model. Finally, open issues and future research directions regarding fog computing and the IoT are discussed.
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Li, Guo, Ma, Mao, and Guan. "Online Workload Allocation via Fog-Fog-Cloud Cooperation to Reduce IoT Task Service Delay." Sensors 19, no. 18 (September 4, 2019): 3830. http://dx.doi.org/10.3390/s19183830.
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Fog computing has recently emerged as an extension of cloud computing in providing high-performance computing services for delay-sensitive Internet of Things (IoT) applications. By offloading tasks to a geographically proximal fog computing server instead of a remote cloud, the delay performance can be greatly improved. However, some IoT applications may still experience considerable delays, including queuing and computation delays, when huge amounts of tasks instantaneously feed into a resource-limited fog node. Accordingly, the cooperation among geographically close fog nodes and the cloud center is desired in fog computing with the ever-increasing computational demands from IoT applications. This paper investigates a workload allocation scheme in an IoT–fog–cloud cooperation system for reducing task service delay, aiming at satisfying as many as possible delay-sensitive IoT applications’ quality of service (QoS) requirements. To this end, we first formulate the workload allocation problem in an IoT-edge-cloud cooperation system, which suggests optimal workload allocation among local fog node, neighboring fog node, and the cloud center to minimize task service delay. Then, the stability of the IoT-fog-cloud queueing system is theoretically analyzed with Lyapunov drift plus penalty theory. Based on the analytical results, we propose a delay-aware online workload allocation and scheduling (DAOWA) algorithm to achieve the goal of reducing long-term average task serve delay. Theoretical analysis and simulations have been conducted to demonstrate the efficiency of the proposal in task serve delay reduction and IoT-fog-cloud queueing system stability.
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Aly, Ahmed H., Atef Ghalwash, Mona M. Nasr, and Ahmed A. Abd-El Hafez. "Formal security analysis of lightweight authenticated key agreement protocol for IoT in cloud computing." Indonesian Journal of Electrical Engineering and Computer Science 24, no. 1 (October 1, 2021): 621. http://dx.doi.org/10.11591/ijeecs.v24.i1.pp621-636.
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The internet of things (IoT) and cloud computing are evolving technologies in the information technology field. Merging the pervasive IoT technology with cloud computing is an innovative solution for better analytics and decision-making. Deployed IoT devices offload different types of data to the cloud, while cloud computing converges the infrastructure, links up the servers, analyzes information obtained from the IoT devices, reinforces processing power, and offers huge storage capacity. However, this merging is prone to various cyber threats that affect the IoT-Cloud environment. Mutual authentication is considered as the forefront mechanism for cyber-attacks as the IoT-Cloud participants have to ensure the authenticity of each other and generate a session key for securing the exchanged traffic. While designing these mechanisms, the constrained nature of the IoT devices must be taken into consideration. We proposed a novel lightweight protocol (Light-AHAKA) for authenticating IoT-Cloud elements and establishing a key agreement for encrypting the exchanged sensitive data was proposed. In this paper, the formal verification of (Light-AHAKA) was presented to prove and verify the correctness of our proposed protocol to ensure that the protocol is free from design flaws before the deployment phase. The verification is performed based on two different approaches, the strand space model and the automated validation of internet security protocols and applications (AVISPA) tool.
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Benomar, Zakaria, Francesco Longo, Giovanni Merlino, and Antonio Puliafito. "Cloud-based Network Virtualization in IoT with OpenStack." ACM Transactions on Internet Technology 22, no. 1 (February 28, 2022): 1–26. http://dx.doi.org/10.1145/3460818.
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In Cloud computing deployments, specifically in the Infrastructure-as-a-Service (IaaS) model, networking is one of the core enabling facilities provided for the users. The IaaS approach ensures significant flexibility and manageability, since the networking resources and topologies are entirely under users’ control. In this context, considerable efforts have been devoted to promoting the Cloud paradigm as a suitable solution for managing IoT environments. Deep and genuine integration between the two ecosystems, Cloud and IoT, may only be attainable at the IaaS level. In light of extending the IoT domain capabilities’ with Cloud-based mechanisms akin to the IaaS Cloud model, network virtualization is a fundamental enabler of infrastructure-oriented IoT deployments. Indeed, an IoT deployment without networking resilience and adaptability makes it unsuitable to meet user-level demands and services’ requirements. Such a limitation makes the IoT-based services adopted in very specific and statically defined scenarios, thus leading to limited plurality and diversity of use cases. This article presents a Cloud-based approach for network virtualization in an IoT context using the de-facto standard IaaS middleware, OpenStack, and its networking subsystem, Neutron. OpenStack is being extended to enable the instantiation of virtual/overlay networks between Cloud-based instances (e.g., virtual machines, containers, and bare metal servers) and/or geographically distributed IoT nodes deployed at the network edge.
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Sadiku, Matthew N. O., Mahamadou Tembely, and Sarhan M. Musa. "Fog Computing: A Primer." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 7 (July 30, 2017): 405. http://dx.doi.org/10.23956/ijarcsse.v7i7.165.
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Fog computing (FC) was proposed in 2012 by Cisco as the ideal computing model for providing real-time computing services and storage to support the resource-constrained Internet of Things (IoT) devices. Thus, FC may be regarded as the convergence of the IoT and the Cloud, combining the data-centric IoT services and pay-as-you-go characteristics of clouds. This paper provides a brief introduction of fog computing.
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Malik, Saadia, Nadia Tabassum, Muhammad Saleem, Tahir Alyas, Muhammad Hamid, and Umer Farooq. "Cloud-IoT Integration: Cloud Service Framework for M2M Communication." Intelligent Automation & Soft Computing 31, no. 1 (2022): 471–80. http://dx.doi.org/10.32604/iasc.2022.019837.
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Lim, Jongbeom. "Scalable Fog Computing Orchestration for Reliable Cloud Task Scheduling." Applied Sciences 11, no. 22 (November 19, 2021): 10996. http://dx.doi.org/10.3390/app112210996.
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As Internet of Things (IoT) and Industrial Internet of Things (IIoT) devices are becoming increasingly popular in the era of the Fourth Industrial Revolution, the orchestration and management of numerous fog devices encounter a scalability problem. In fog computing environments, to embrace various types of computation, cloud virtualization technology is widely used. With virtualization technology, IoT and IIoT tasks can be run on virtual machines or containers, which are able to migrate from one machine to another. However, efficient and scalable orchestration of migrations for mobile users and devices in fog computing environments is not an easy task. Naïve or unmanaged migrations may impinge on the reliability of cloud tasks. In this paper, we propose a scalable fog computing orchestration mechanism for reliable cloud task scheduling. The proposed scalable orchestration mechanism considers live migrations of virtual machines and containers for the edge servers to reduce both cloud task failures and suspended time when a device is disconnected due to mobility. The performance evaluation shows that our proposed fog computing orchestration is scalable while preserving the reliability of cloud tasks.
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Detti, Andrea, Hidenori Nakazato, Juan Antonio Martínez Navarro, Giuseppe Tropea, Ludovico Funari, Luca Petrucci, Juan Andrés Sánchez Segado, and Kenji Kanai. "VirIoT: A Cloud of Things That Offers IoT Infrastructures as a Service." Sensors 21, no. 19 (September 30, 2021): 6546. http://dx.doi.org/10.3390/s21196546.
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Many cloud providers offer IoT services that simplify the collection and processing of IoT information. However, the IoT infrastructure composed of sensors and actuators that produces this information remains outside the cloud; therefore, application developers must install, connect and manage the cloud. This requirement can be a market barrier, especially for small/medium software companies that cannot afford the infrastructural costs associated with it and would only prefer to focus on IoT application developments. Motivated by the wish to eliminate this barrier, this paper proposes a Cloud of Things platform, called VirIoT, which fully brings the Infrastructure as a service model typical of cloud computing to the world of Internet of Things. VirIoT provides users with virtual IoT infrastructures (Virtual Silos) composed of virtual things, with which users can interact through dedicated and standardized broker servers in which the technology can be chosen among those offered by the platform, such as oneM2M, NGSI and NGSI-LD. VirIoT allows developers to focus their efforts exclusively on IoT applications without worrying about infrastructure management and allows cloud providers to expand their IoT services portfolio. VirIoT uses external things and cloud/edge computing resources to deliver the IoT virtualization services. Its open-source architecture is microservice-based and runs on top of a distributed Kubernetes platform with nodes in central and edge data centers. The architecture is scalable, efficient and able to support the continuous integration of heterogeneous things and IoT standards, taking care of interoperability issues. Using a VirIoT deployment spanning data centers in Europe and Japan, we conducted a performance evaluation with a two-fold objective: showing the efficiency and scalability of the architecture; and leveraging VirIoT’s ability to integrate different IoT standards in order to make a fair comparison of some open-source IoT Broker implementations, namely Mobius for oneM2M, Orion for NGSIv2, Orion-LD and Scorpio for NGSI-LD.
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Dr. M. Duraipandian. "Ranked k-NN Crowdsourced Model for Cloud Internet of Things (CIoT)." Journal of ISMAC 2, no. 3 (July 10, 2020): 173–80. http://dx.doi.org/10.36548/jismac.2020.3.006.
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Internet of Things (IoT) has gained more attention in recent years and its influence over future internet is projected to be more as a promising technology. IoT enables sensors to merge with smart devices to monitor, observe and analyse the real time data. These features make the IoT, a suitable technology, for smart applications. On the other hand, cloud offers a better computing paradigm to store and analyse the data. Cloud reduces the complexities in day today life with its novel applications and services, in an efficient manner. However, present IoT and Cloud solutions are focused towards centralized solutions, which limits the user capacity. To enrich the Cloud integrated IoT benefits, a flexible large-scale data collection and analysis is introduced as crowdsourcing, which provides a new dimension in data mining applications. This research work presents a cloud computing crowdsourced data analysis model implemented over IoT, to obtain better computation speed with improved sensitivity, specificity and accuracy.
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Salikhov, R. B., V. Kh Abdrakhmanov, and I. N. Safargalin. "Internet of Things (IoT) Security Alarms on ESP32-CAM." Journal of Physics: Conference Series 2096, no. 1 (November 1, 2021): 012109. http://dx.doi.org/10.1088/1742-6596/2096/1/012109.
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Abstract The article presents the basic requirements for systems operating on the technology of the industrial / industrial "Internet of Things" (Industrial Internet of Things, IIoT). presents the main technologies with which it is recommended to develop IIoT devices. These are low-level programming of microcontrollers using the STM32 example, working with real-time systems (using Mbed OS as an example), using low-power wireless technologies, such as LoRa, 6LoWPAN, NB-IoT, ZigBee, Bluetooth Low Energy (BLE). It is also necessary to use special protocols, for example, the MQTT application layer protocol, the use of special cloud services, for example, Artik Cloud, IBM Cloud, Intel Cloud. The article also provides the main features of the choice of hardware - a development board for a microcontroller, wireless communication modules, as well as features of choosing software to accelerate the stage of initial debugging and development of a device prototype. It also provides a brief overview of existing security alarm solutions based on the Internet of Things (IoT) and Smart Home technologies. The idea of creating a budget solution based on Arduino and ESP32-CAM is presented. A prototype was assembled, the device was tested in operation.
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Xiang, Feng, and Ye Fa Hu. "Cloud Manufacturing Resource Access System Based on Internet of Things." Applied Mechanics and Materials 121-126 (October 2011): 2421–25. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.2421.
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The cloud manufacturing (CloudM) resource access solution of Internet of Things (IOT) application was discussed. According to resource access requirements, a kind of CloudM resource access architecture based on IOT was described, as well as several key technologies in the architecture. Several key issues such as classification of resource information accesses, access processes were studied. Related explanations about QoS information expanding, manufacturing capacity information constructing, EPC information collection were illustrated. With magnetic bearing as an example, its conceptual information model and QoS expanded information described by PML were given.
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Anwar, Mohammad Kasyful, and Tjahjanto. "Perancangan Database IoT Berbasis Cloud dengan Restful API." Techno.Com 20, no. 2 (May 19, 2021): 268–79. http://dx.doi.org/10.33633/tc.v20i2.4322.
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Internet of Things (IoT) memiliki potensi besar di era industry 4.0, saat mulai muncul beberapa produk elektronik rumah tangga berbasis IoT seperti lampu, saklar, stop-kontak dan lainnya, dengan IoT perangkat rumah tangga tersebut bisa dikendalikan dan dipantau dari jarak jauh sehingga lebih memudahkan penggunanya. Penyimpanan data IoT berbasis cloud menimbulkan permsalahan keamanan data dan performa throughput pada server. Dalam paper ini dibahas mengenai rancangan database berbasis cloud dengan restful API untuk IoT agar data IoT aman dan memiliki throughput yang bagus dengan struktur data yang diatur pada database.
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Dang, L. Minh, Md Jalil Piran, Dongil Han, Kyungbok Min, and Hyeonjoon Moon. "A Survey on Internet of Things and Cloud Computing for Healthcare." Electronics 8, no. 7 (July 9, 2019): 768. http://dx.doi.org/10.3390/electronics8070768.
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The fast development of the Internet of Things (IoT) technology in recent years has supported connections of numerous smart things along with sensors and established seamless data exchange between them, so it leads to a stringy requirement for data analysis and data storage platform such as cloud computing and fog computing. Healthcare is one of the application domains in IoT that draws enormous interest from industry, the research community, and the public sector. The development of IoT and cloud computing is improving patient safety, staff satisfaction, and operational efficiency in the medical industry. This survey is conducted to analyze the latest IoT components, applications, and market trends of IoT in healthcare, as well as study current development in IoT and cloud computing-based healthcare applications since 2015. We also consider how promising technologies such as cloud computing, ambient assisted living, big data, and wearables are being applied in the healthcare industry and discover various IoT, e-health regulations and policies worldwide to determine how they assist the sustainable development of IoT and cloud computing in the healthcare industry. Moreover, an in-depth review of IoT privacy and security issues, including potential threats, attack types, and security setups from a healthcare viewpoint is conducted. Finally, this paper analyzes previous well-known security models to deal with security risks and provides trends, highlighted opportunities, and challenges for the IoT-based healthcare future development.
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Rath, Mamata, and Bibudhendu Pati. "Security Assertion of IoT Devices Using Cloud of Things Perception." International Journal of Interdisciplinary Telecommunications and Networking 11, no. 4 (October 2019): 17–31. http://dx.doi.org/10.4018/ijitn.2019100102.
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Adoption of Internet of Things (IoT) and Cloud of Things (CoT) in the current developing technology era are expected to be more and more invasive, making them important mechanism of the future Internet-based communication systems. Cloud of Things and Internet of Things (IoT) are two emerging as well as diversified advanced domains that are diversified in current technological scenario. Paradigm where Cloud and IoT are merged together is foreseen as disruptive and as an enabler of a large number of application scenarios. Due to the adoption of the Cloud and IoT paradigm a number of applications are gaining important technical attention. In the future, it is going to be more complicated a setup to handle security in technology. Information till now will severely get changed and it will be very tough to keep up with varying technology. Organisations will have to repeatedly switch over to new skill-based technology with respect to higher expenditure. Latest tools, methods and enough expertise are highly essential to control threats and vulnerability to computing systems. Keeping in view the integration of Cloud computing and IoT in the new domain of Cloud of things, the said article provides an up-to-date eminence of Cloud-based IoT applications and Cloud of Things with a focus on their security and application-oriented challenges. These challenges are then synthesized in detail to present a technical survey on various issues related to IoT security, concerns, adopted mechanisms and their positive security assurance using Cloud of Things.
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Gassara, Mouna, Manel Elleuchi, and Mohamed Abid. "Cloud-based platforms for LoRa internet of things: a survey." International Journal of Informatics and Communication Technology (IJ-ICT) 10, no. 1 (April 1, 2021): 54. http://dx.doi.org/10.11591/ijict.v10i1.pp54-64.
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<span><span>Internet of Things</span> (IoT) establishes a smart communication system between the human being and the surrounding objects (or “things”) while using the internet as the backbone of this system. Cloud is the fundamental constituent of IoT. It offers important application services in numerous <span>application domains</span>. Indeed, many IoT cloud platforms are competing to provide appropriate and very specific IoT services. The LoRa platform in particular presents a long-range, low-bit rate, low-power, wireless telecommunication protocol for IoT. As such, end-devices make use of LoRa through a sole wireless hop in order to communicate to the gateway(s) that is (are) considered as relay messages and transparent bridges between these end-devices and an IoT cloud while connecting to the Internet. This article surveys the most used IoT <span>cloud platforms</span> suitable for the LoRa communication protocol through a deep and detailed study of previously published works related to this topic. Moreover, a comparison is made between these IoT cloud platforms according to their characteristics and application domains. The overall aim of the present paper is to provide researchers in the field with detailed knowledge concerning the IoT <span>cloud platforms appropriate to the LoRa communication system </span>including the advantages and drawbacks of each one of them.</span>
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Verma, Jyotsna. "Enabling Internet of Things through Sensor Cloud: A Review." Scalable Computing: Practice and Experience 22, no. 4 (November 24, 2021): 445–62. http://dx.doi.org/10.12694/scpe.v22i4.1878.
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With the inception of the Internet of Things (IoT), wireless technology found a new outlook where the physical objects can interact with each other and can sense the environment. The IoT has found its way in the real world and has connected billions of devices throughout the world. However, its limitations, such as limited processing capability, storage capability, security and privacy issues, and energy constraints prevent the IoT system to be properly utilized by the real-world applications. Hence, the integration of IoT with various emerging technologies like big data, software defined networks, machine learning, fog computing, sensor cloud, etc., will make the IoT system a more powerful technology. The sensor cloud provides an open, secure, flexible, large storage and a computational capable infrastructure which makes the ensemble architecture of IoT and sensor cloud more efficient. An extensive review of the IoT system enabled sensor cloud is presented in the paper, and with this context, the paper attempts to summarize the sensor cloud infrastructure along with its challenges. In addition, the paper presents the possible integrated architecture of the IoT and the sensor cloud which enables the network to be properly utilized. Further, the importance of integrating these two promising technologies and research challenges associated with it is also identified. Finally, the paper analyses and discusses the motivation behind the ensemble system along with future research direction.
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Anawar, Muhammad Rizwan, Shangguang Wang, Muhammad Azam Zia, Ahmer Khan Jadoon, Umair Akram, and Salman Raza. "Fog Computing: An Overview of Big IoT Data Analytics." Wireless Communications and Mobile Computing 2018 (2018): 1–22. http://dx.doi.org/10.1155/2018/7157192.
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A huge amount of data, generated by Internet of Things (IoT), is growing up exponentially based on nonstop operational states. Those IoT devices are generating an avalanche of information that is disruptive for predictable data processing and analytics functionality, which is perfectly handled by the cloud before explosion growth of IoT. Fog computing structure confronts those disruptions, with powerful complement functionality of cloud framework, based on deployment of micro clouds (fog nodes) at proximity edge of data sources. Particularly big IoT data analytics by fog computing structure is on emerging phase and requires extensive research to produce more proficient knowledge and smart decisions. This survey summarizes the fog challenges and opportunities in the context of big IoT data analytics on fog networking. In addition, it emphasizes that the key characteristics in some proposed research works make the fog computing a suitable platform for new proliferating IoT devices, services, and applications. Most significant fog applications (e.g., health care monitoring, smart cities, connected vehicles, and smart grid) will be discussed here to create a well-organized green computing paradigm to support the next generation of IoT applications.
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Kertesz, A., T. Pflanzner, and T. Gyimothy. "A Mobile IoT Device Simulator for IoT-Fog-Cloud Systems." Journal of Grid Computing 17, no. 3 (October 25, 2018): 529–51. http://dx.doi.org/10.1007/s10723-018-9468-9.
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A, Amulya. "IOT Based Cloud Integrated Smart Classroom for Sustainable Campus." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (July 30, 2021): 3002–8. http://dx.doi.org/10.22214/ijraset.2021.36893.
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Recently, smart classroom technology, students are more demanding innovative university campus life, and are willing to use creative learning methods. IOT and Cloud computing technologies will provide solutions for smart and a sustainable campus to boost learning methods of the students and improve the efficiency of everyday activities within the Institution. This paper focuses on the IOT paradigm within the teaching process with the mix of Cloud for education system. IOT in education will provide student to be told new technologies that helps the students to create new ideas and logical for the social problems. IOT based cloud computing technology will provide intelligence system, unified campus portal services, security and maintenance system. IOT devices are being employed to trace students who Skip their classes, send alerts help students to concentrate academic work regularly, and to hunt out lost personal items. The hardware component of IOT includes microcontroller board, sensor module, and wireless and wired connections. Using this software module the knowledge to and from sensor modules is processed and then transmitted to the cloud storage. Our paper describes how efficiently IOT and Cloud Infrastructure restructure the quality education and learning methods.
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Valeti, Nagarjuna, and V. Ceronmani Sharmila. "Fault Detection based Connected Dominating Set (FDCDS) in Fog Computing." Webology 17, no. 2 (December 21, 2020): 599–606. http://dx.doi.org/10.14704/web/v17i2/web17054.
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The meaning of cloud computing is providing services by using the internet. From the Cloud Data Centres (CDC) the services are utilized by the cloud users. Presently (Internet of things) IOT playing the key role to improve the performance of the fog computing enabled applications. Migrating the wireless sensor networks with IOT becomes the most powerful and error free application based on the availability of the services, cloud storage, computation and these are transferred efficiently between server and cloud. Health domain is most widely affecting system in cloud computing as well as by using fog computing with IOT. The system causes various failures for providing the service continuously. Enabling the fog computing with the integration of cloud for the medical devices to transmit the patient information to the cloud storage has become the complicated for the IOT sensors continuously. This may cause the data loss and also reduce the performance of the medical device. To improve the continuous services within the cloud server. In this paper, the Fault detection based Connected Dominating Set (FDCDS) which provides the continuous services with the integration of fog computing and IOT devices with wireless sensor networks. Simulation shows the performance of the proposed system.
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Anand, Sakshi, and Avinash Sharma. "Issues and Concerns in Security of Cloud Environment in Internet of Things." Journal of Computational and Theoretical Nanoscience 16, no. 10 (October 1, 2019): 4374–78. http://dx.doi.org/10.1166/jctn.2019.8528.
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Internet of Things (IoT) is a permeative affair that is gaining heights with every passing day thus changing the way society has been living till now. Living in an era where every “thing” will be connected to the Internet is no more a dream. Now we can see people using IoT on daily basis like in the field of education, agriculture, transportation, healthcare, science and many more. Ranging from smart watches to automated machines in industries people have started using IoT for both personal and commercial purposes. With the talk of linking devices to the Internet comes the concept of Cloud. Before IoT was revolutionized, the main purpose of Cloud was to act upon relentless task involving factors like scalability, elasticity, adaptability and multitenancy. But as Internet of Things started gaining heights, there was a need to fulfill the demand of responding and managing issues and outcomes on the go, thus enhancing the features of Cloud making it omnipresent, nimble and flexible on demand. Now remotely tasks such as configuring, reviewing, updating, accessing the condition, extracting data etc. on IoT devices can be easily performed. But this added ease from the IoT Cloud exposed the IoT devices to various risks. In this paper we will be discussing different security issues that arise in IoT devices if the IoT Cloud gets compromised.
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Tahir Alyas, Tahir Alyas. "Data Breaches Security Issues for Cloud Based Internet of Things." International Journal for Electronic Crime Investigation 2, no. 1 (March 8, 2018): 7. http://dx.doi.org/10.54692/ijeci.2018.02017.
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Now a day’s Internet of Things (IoT) and cloud computing are latest popular technologies. Both technologies have great role in our life. Their adoption and utilization are relied upon increasingly inescapable and making them vital segments of the Future Internet. A novel worldview where Cloud and IoT are consolidated and would be helpful for large number of application scenarios. Security in cloud computing and IoT truly challenging, needs a watchful comprehension and it includes numerous zones. Protections of cloud situations can be more powerful, versatile and have a superior financially savvy, yet the vast centralization of assets and information is a more appealing focus for aggressors. In this paper, data breaches architecture for the next generation technologies on cloud-based IoT will be introduced which will address the challenging issues of data breaches in cloud base system.
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Tawalbeh, Lo’ai, Fadi Muheidat, Mais Tawalbeh, and Muhannad Quwaider. "IoT Privacy and Security: Challenges and Solutions." Applied Sciences 10, no. 12 (June 15, 2020): 4102. http://dx.doi.org/10.3390/app10124102.
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Privacy and security are among the significant challenges of the Internet of Things (IoT). Improper device updates, lack of efficient and robust security protocols, user unawareness, and famous active device monitoring are among the challenges that IoT is facing. In this work, we are exploring the background of IoT systems and security measures, and identifying (a) different security and privacy issues, (b) approaches used to secure the components of IoT-based environments and systems, (c) existing security solutions, and (d) the best privacy models necessary and suitable for different layers of IoT driven applications. In this work, we proposed a new IoT layered model: generic and stretched with the privacy and security components and layers identification. The proposed cloud/edge supported IoT system is implemented and evaluated. The lower layer represented by the IoT nodes generated from the Amazon Web Service (AWS) as Virtual Machines. The middle layer (edge) implemented as a Raspberry Pi 4 hardware kit with support of the Greengrass Edge Environment in AWS. We used the cloud-enabled IoT environment in AWS to implement the top layer (the cloud). The security protocols and critical management sessions were between each of these layers to ensure the privacy of the users’ information. We implemented security certificates to allow data transfer between the layers of the proposed cloud/edge enabled IoT model. Not only is the proposed system model eliminating possible security vulnerabilities, but it also can be used along with the best security techniques to countermeasure the cybersecurity threats facing each one of the layers; cloud, edge, and IoT.
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Molnár, Ján, Simona Kirešová, Tibor Vince, Dobroslav Kováč, Patrik Jacko, Matej Bereš, and Peter Hrabovský. "Weather Station IoT Educational Model Using Cloud Services." JUCS - Journal of Universal Computer Science 26, no. 11 (November 28, 2020): 1495–512. http://dx.doi.org/10.3897/jucs.2020.079.
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IoT technology is gaining more and more popularity in practice, as it collects, processes, evaluates and stores important measured data. The IoT is used every day in the work, in the home or smart houses or in public areas. It realizes the connectivity between real world and digital world which means, that it converts physical quantities of the real world in the form of analog signals into digital numbers stored in clauds. It is essential that students gain practical experience in the design and implementation of the IoT systems during their studies. The article first describes IoT issues and communication protocols used in IoT generally are closer described. Then the design and implementation of an educational model of IoT system - Weather station with the ThingSpeak cloud support is described. The created IoT model interconnects microcontroller programming, sensors and measuring, cloud API interfaces, MATLAB scripts which are useful to analyses the stored data, Windows and Android application developing.
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Capella, J. V., Alberto Bonastre, Rafael Ors, and Miguel Peris. "A New Application of Internet of Things and Cloud Services in Analytical Chemistry: Determination of Bicarbonate in Water." Sensors 19, no. 24 (December 14, 2019): 5528. http://dx.doi.org/10.3390/s19245528.
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In a constantly evolving world, new technologies such as Internet of Things (IoT) and cloud-based services offer great opportunities in many fields. In this paper we propose a new approach to the development of smart sensors using IoT and cloud computing, which open new interesting possibilities in analytical chemistry. According to IoT philosophy, these new sensors are able to integrate the generated data on the existing IoT platforms, so that information may be used whenever needed. Furthermore, the utilization of these technologies permits one to obtain sensors with significantly enhanced features using the information available in the cloud. To validate our new approach, a bicarbonate IoT-based smart sensor has been developed. A classical CO2 ion selective electrode (ISE) utilizes the pH information retrieved from the cloud and then provides an indirect measurement of bicarbonate concentration, which is offered to the cloud. The experimental data obtained are compared to those yielded by three other classical ISEs, with satisfactory results being achieved in most instances. Additionally, this methodology leads to lower-consumption, low-cost bicarbonate sensors capable of being employed within an IoT application, for instance in the continuous monitoring of HCO3− in rivers. Most importantly, this innovative application field of IoT and cloud approaches can be clearly perceived as an indicator for future developments over the short-term.
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Fajjari, Ilhem, Fouad Tobagi, and Yutaka Takahashi. "Cloud edge computing in the IoT." Annals of Telecommunications 73, no. 7-8 (August 2018): 413–14. http://dx.doi.org/10.1007/s12243-018-0651-6.
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GHILIC-MICU, Bogdan, Marinela MIRCEA, and Marian STOICA. "QAaaS in a Cloud IoT Ecosystem." Informatica Economica 21, no. 4/2017 (December 30, 2017): 5–14. http://dx.doi.org/10.12948/issn14531305/21.4.2017.01.
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